Mail Network Optimization Project

Mail Network Optimization Project

New Delhi, November 23, 2010Interaction with the Staff Side

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The Background

External Factors▪ Declining mail volumes

▪ Competition from Domestic and Inter-

national players

▪ Absence of regulation

▪ Change in mail profile

▪ Customer Demands(e.g. Track & Trace)

Systemic Issues▪ Difficulties of existing

mail network vis-à-vis changed mail profile

▪ Low level of IT induction in mail processing

▪ Low productivity and ageing workforce

▪ Delivery inconsistencies and visibility

▪ Lack of customer focus

Impact

▪ Inconsistent quality of service

▪ High operational costs

▪ Eroding customer base

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The Scope of Project

"Get the core right"

"Modernise the look and feel"

▪ Optimise India Post's network from collection to delivery

▪ Standardize processes with focus on significant quality improvement & reduction in network complexity

▪ Put in place an effective performance measurement system through regular reviews

▪ Improve the ambience of mail offices ▪ Upgrade processing facilities and improve

working conditions for employees ▪ Make staff and customers proud of being

associated with India Post

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The Approach

PRO

JECT

APP

ROAC

HStart with limited product range for prioritised cities

Increase the product range for these prioritised cities

Expand to all India for all products

▪ Early pilot and broad involvement of field units

▪ Rigorous monitoring

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The Project Plan G

eogr

aphi

cal r

each

Speed Post & International mail

Ist class IInd class

Product range

Prioritycities

All India

2011

2012

Scenario-based designand pilots

Scenario-based design

Roll-out

2010"Wave 1"

Approach reflects a strong need for immediate tangible impact

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Project Waves for Speed Post

SOURCE: Mail Network Optimisation Project

Wave 1 Wave 2 Wave 3

Cities in scope

Timeline ▪ March-July ▪ August-September ▪ September-November

▪ Mumbai

▪ Delhi

▪ Kolkata

▪ Chennai

▪ Bangalore

▪ Hyderabad

▪ Noida

▪ Gurgaon

▪ Pune

▪ Mysore

▪ Howrah

▪ Bhopal

▪ Trivandrum

▪ Chandigarh

▪ Nagpur

▪ Ahmedabad

▪ Patna

▪ Kochi

▪ Lucknow

8 5 6

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Optimization of delivery in wave 2 (1st class mail) as SpeedPost only accounts for ~10% of delivery volume

Network optimisation: Key Operational Areas (Speed Post)


▪ What are the right processes within the facility?– How to ensure standardisation?– How to maximize productivity and quality?

▪ What is the right network schedule? – Which cut-off times and processing windows at each processing step across the value chain would facilitate next day delivery?

▪ How to measure India Post's performance?– How is the share of next day delivery (D+1)?– Track & Trace: Are 100% scans ensured

across the network?

▪ What is the right network topolgy?– How many processing SPCs do we need

within one city (and where)?– How many sorting hubs do we need

across cities (and where)?

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Initial Impact of the Project in terms of Operational Improvement

Easier sorting – Ensure minimum multiple handling

Less workload – reduce no. of bags & missorts between different locations

Better equipment – Ease of working for staff at SPCs with new equipments

Higher throughput – Ensure higher processing with improved process design

Streamlined workflow – by having optimised inflow of mails in the processing centersPrioritized processing – Ensure processing prioritisation based on the time of the day for maximum connectivity

Keep everyone informed – Regular interaction and display of SPC's daily performance, suggestions and feedback encouragedTraining & Incentives – Incentivise high performers and help all staff with newly developed training modules


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The project has witnessed significant changes

▪ International EMS: IT interface fixed (19:59 timestamp) ~Rs. 1.5

crore revenue recovery

▪ D+x performance in 6 metros improved by

~1.0 day over last months

▪ Productivity and throughput improved

across centres by more than 50%

▪ Comprehensive set of 18 KPIs for Speed

Post developed, scorecards and VCs

institutionalised

▪ Detailed Speed Post Manual developed to

ensure standardi-sation of processes

across India

▪ Quality management cells institutionalized

▪ Network schedules in 6 metros revised using comprehensive model

▪ Instructions to merge international EMS

inbound network with Speed Post issued

▪ Multiple sorting at SPC "outlets" reduced, e.g.,

Bangalore (6 sub hubs), Mumbai (GPO

volumes)

▪ Network topology model developed with

revision of sorting hubs from 315 to 89

▪ Integrated SpeedPost database being

developed

▪ Directorate rigorously monitoring the

progress through score card

▪ All CPMGs involved (focus until date on 8 circles) and actively

participating

▪ Performance dialogues initiated on

a daily basis across the organisation

▪ New equipment tested and introduced

to improve working conditions (e.g., roller

containers, revised sorting cases, roller trays, bag scissors)

▪ Project has brought comprehensive look

at the all the stakeholders

▪ Comprehensive Look and Feel workstream

initiated and institutionalized (run

by BD team)

Quality/performance improvement

Quality/performance improvement

Financial improvements

Financial improvements Complexity reductionComplexity reduction Proud to be part of

India PostProud to be part of

India PostChanges in day-to-day

lifeChanges in day-to-day

life

Soft factsHard facts

11 33

55

66

44

99

1010

1111

1313

1414

1818

1919


1212

2020

77

1616

1515

88

1717

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Number of Speed Post Centres

Number of final selections at each Speed Post Centre

Number of bags closed across Speed

Post Centres

Sorting complexities necessitated changes in the operational network for Speed Post


1 Assuming that there is at least one mail from every NSPC to every other NSPC

314Selections

315NSPCs 315 314 98,9101=

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Input components of the network topology model


Locationinformation

Volumedata

Air/roadconnections

Cut-offtimes

Simulationof mail flow in the network

Inputs Outputs

Processing

D+xpercentage

NSPC-POmapping

Volumeflows

Throughputrequirements

For differentnumber of NSPCs

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Basic NSPC and Post Office information

Data type Source

▪ Classification of NSPCs done based on population

▪ Population figures taken from 2001 census reports

▪ Urban: Population >5 lakhs e.g., Delhi, Mumbai

▪ Rural: Population <5 lakhs e.g., Pauri, Vashi

Urban/rural classification

of NSPCs

Data characteristics

▪ List of NSPCs and delivery POs covered by Speed Post

taken from the official Speed Post Directory

▪ Consistency checks on NSPCs done by BD

Directorate

List of NSPCs and Delivery Post Offices1

▪ 315 NSPCs

▪ delivery POs with unique pin codes

▪ Mapping of POs to corresponding NSPCs


1 SSPCs have not been considered for comprehensively modelling as they do not play a role in arriving at an optimal NSPC – PO mapping

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Coordinates (Latitude / Longitude)

62.0

23.03.0

100.0

Missing coordinates

Questionable2 coordinates

12.0

Unique coordinates

Duplicate1 coordinates

All coordinates

Post Office coordinates and booking/delivery volume


Percent of average daily booking volumes

Used for modelling as is PO coordinates assumed to be same as NSPC coordinates

Booking / Delivery Volumes

▪ Booking/delivery volume information at the post office level is used to split the “from-to” NSPC volume matrix (previous page) between the POs

▪ For post offices for which no volume information is available, the average daily booking and delivery volumes are assumed to be 1

Source ▪ Coordinate

▪ Volume

: http://itouchmap.com/latlong.html

: Jan - Apr 2010 PO level data from Speed Net

85% of data is usable which is sufficient for the

purpose of modeling

1 Duplicate coordinates exist since India (specially rural areas) is not yet completely mapped by latitude/longitude providers2 The distance between PO and corresponding NSPC is more than 200 km as per the coordinates

Note: 100% = 10 million per month

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Air connections


Airports

▪ List of ~70 domestic airports in India picked up from a global list of airports

▪ Latitude/longitude information taken from http://itouchmap.com/latlong.html

Flights

▪ List of 6,633 domestic flights collected from airlines

▪ Flights mapped to airports in the above airport list

Loading/Unloading

Times

Loading time, hours

Airport category

Unloading time, hours

Airports classified in 3 categories

based on domestic cargo

traffic

A 2.0 1.5

B 1.5 1.0

C 1.0 0.5

Example

Bangalore

Bhopal

Dibrugarh

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Road connections


Factor Assumption Reasoning

▪ Air distances calculated based on latitude/

longitude information

▪ Air distances multiplied by detour factors

Distances

▪ Standard practice for distance calculation

▪ Detour factors taken based on

sample calculations for a

few NSPCs

Detour factorUrban

1.45

Rural1.25

▪ Separate MMS speeds assumed for rural and urban NSPC-PO travel

▪ All NSPC-NSPC travel is assumed to be rural

MMS Speed

▪ Based on inputs from the field

Urban20 km/hr

Rural35 km/hr

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Cut-off times (1/2)


Parameter Explanation

▪ Time at which MMS vehicles leave booking post

offices to take articles to origin NSPCs

▪ All articles booked after this cut-off are assumed to be

booked the next day

Cut-off from POs

▪ Majority of post offices do not work beyond 16:00 hrs

but there are a few post offices which

offer booking up to 19:00 hrs2 or later

▪ Latest time by which MMS vehicles carrying articles

from the destination NSPCs reach the delivery post

offices

▪ Articles that arrive at the delivery post office after this cut-off, will not be delivered the same day

▪ Second delivery rounds have been

introduced in the 6 metros

▪ Only single delivery round is feasible in rural areas because

of long distance

Cut-off to POs1

Reasoning

Metros13:00 hrs

Rest09:00 hrs

Assumption

1 MMS vehicles leave the destination NSPCs 3 hours before this cut-off i.e. at 10:00 hrs for urban POs and at 06:00 hrs for rural Pos2 Only for 6 metros which have 2nd delivery round. 1900 cut off doesn’t mean commitment to customer. Not all mail booked till 1900 would be delivered in D+1

19:00 hrs

Scenarios16:00 hrs

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Cut-off times (2/2)


Parameter Explanation

▪ Time at which articles leave origin NSPC to be taken (by flight/road) to

destination NSPC

▪ Articles unable to be processed at the origin

NSPC by this cut-off, will not be connected on the

same day

Cut-off between

NSPCs

Reasoning

Options20:00 hrs

21:00 hrs

01:00 hrs

Processing time

A processing time of 120 minutes is

assumed at both origin and destination

NSPC

Articles need to arrive 2 hours before the cut-offs to

be able to get processed and connected the same

day

Assumption

▪ Right cut-off time can vary

depending on number of NSPCs

and hence need to be optimized

02:00 hrs

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Inputs to the model

Contents

Working of the model

Outputs of the model

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Configuration Comparison

Output of the network topology model – Scenario 1


0

10

20

30

40

50

60

70

80

90

100

0 45 90 135 180 225 270 315

QualityPercentage

No. of NSPCs

No. of sorting hubs ‘D+1’ %

‘D+1 plus D+2’ %

Network Complexity1

20 42.74% 62.19% 0.42%

70 56.63% 84.70% 5.10%

80 57.91% 85.95% 6.66%

90 58.54% 87.19% 8.43%

100 59.51% 88.38% 10.41%

110 60.33% 91.24% 12.59%

120 61.42% 90.69% 14.98%

130 61.51% 92.25% 17.59%

140 62.58% 93.53% 20.40%

150 63.00% 94.28% 23.41%

310 66.74% 98.68% 100.00%

‘D+1’ %

‘D+1 plusD+2’ %

Networkcomplexity

▪ Cut-off from POs : 16:00 hrs▪ Cut-off between NSPCs : 21:00 hrs

▪ Second delivery round : for all urban POs

1 Measured in terms of number of bags closed in a day assuming 1 bag from every

sorting hub to every other sorting hub

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0

10

20

30

40

50

60

70

80

90

100

0 45 90 135 180 225 270 315

QualityPercentage

No. of NSPCs


‘D+1 plus D+2’ %

Network Complexity1

20 38.13% 62.57% 0.42%

70 48.79% 79.95% 5.10%

80 49.23% 83.97% 6.66%

90 50.26% 86.29% 8.43%

100 50.97% 87.97% 10.41%

110 51.57% 88.53% 12.59%

120 52.37% 91.09% 14.98%

130 53.03% 92.48% 17.59%

140 53.41% 92.28% 20.40%

150 53.91% 93.36% 23.41%

310 56.83% 98.46% 100.00%

‘D+1’ %

‘D+1 plusD+2’ %

Networkcomplexity


▪ Second delivery round : for all urban POs



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0

10

20

30

40

50

60

70

80

90

100

0 45 90 135 180 225 270 315

QualityPercentage

No. of NSPCs


‘D+1 plus D+2’ %

Network Complexity1

20 41.34% 66.74% 0.42%

70 52.40% 84.43% 5.10%

80 53.36% 85.61% 6.66%

90 55.18% 87.24% 8.43%

100 55.93% 88.98% 10.41%

110 57.31% 91.08% 12.59%

120 57.47% 91.76% 14.98%

130 57.98% 92.38% 17.59%

140 58.62% 92.85% 20.40%

150 59.47% 94.10% 23.41%

310 62.62% 97.89% 100.00%

‘D+1’ %

‘D+1 plusD+2’ %

Networkcomplexity


▪ Second delivery round : for POs in the 6 metros



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0

10

20

30

40

50

60

70

80

90

100

0 45 90 135 180 225 270 315

QualityPercentage

No. of NSPCs


‘D+1 plus D+2’ %

Network Complexity1

20 37.12% 65.35% 0.42%

70 44.28% 83.92% 5.10%

80 44.94% 84.32% 6.66%

90 45.72% 85.98% 8.43%

100 46.30% 87.02% 10.41%

110 46.53% 88.50% 12.59%

120 47.29% 89.88% 14.98%

130 47.71% 90.58% 17.59%

140 48.02% 91.46% 20.40%

150 48.46% 92.52% 23.41%

310 51.32% 97.25% 100.00%

‘D+1’ %

‘D+1 plusD+2’ %

Networkcomplexity


▪ Second delivery round : for POs in the 6 metros



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Deciding the ‘right’ number of sorting hubs

1 Measured in terms of ‘D+1’ % as per the network topology model2 Measured in terms of number of bags closed in a day assuming 1 bag from every sorting hub to every other sorting hub


Subjective trade-off between structural

quality and operational ease

No. of sorting hubs

Structuralquality1

Operational complexity2

80 45% 7%

140 48% 20%

Better quality due to improved

network structure…

…will be compensated by delays due to increased operational complexity

310 51% 100%

Fact

or ~

3.0

‘Right’number of

sorting hubs?

ILLUSTRATIVE

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Other outputs provided by the model


▪ List of sorting hubs

▪ Mapping of post offices to sorting hubs

▪ Expected daily volumes at sorting hubs

▪ Volume flows between sorting hubs

▪ Expected throughput requirements at sorting hubs

Note: The above outputs are provided for specific configurations

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New Speed Post Operational Network


▪ 89 Sorting Hubs

▪ Sorting hubs: Location and number arrived at through a comprehensive modelling

▪ Only Sorting Hubs to close bags for each other, only a few intra-Circle hubs allowed

▪ Booking interface not reduced

▪ Overall expedited processing, transit and delivery time, reduced sorting complexity (back-routing to a small fraction of mail notwithstanding)

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Inter-national reports


Scan com-pliance reports

Transit analysis within city

Transit analysis across city

Time per leg of transit within city

Time per leg of transit across city

Scans compliance in the entire network

Scan analysis per leg of transit within city

Scan analysis per leg of transit across city

Percent of F-scans in SpeedNet vs. F-scans in IPS1

Share of SpeedNet Delivery scans vs. IPS F-scans (TBD)

Articles processed per hour per FTE

Staff absenteeism

Share of bags without bag labels

Share of articles not processed in SpeedNet

Share of articles closed after cut-off time

Share of missorted articles

Share of articles with missing pin codes

Share of articles not dispatched same set

Percent of F-scans in IPS vs. D-scans in IPS

D+X reports

KPI What does it do?

Measures for international inbound article the efficiency of movement at every step before

merger with Speed Post

Support-ing KPIs

Measures for each processing step whether articles got

scanned as prescribed

Measures speed and reliability of processing of Speed Post articles

from booking to delivery

Supports achieving better D+x and scan performance

1a

1b

1c

1d

2a

2b

2c

3a

3c

4a

4b

4c

4d

4e

4f

4g

4h

3b

Key Performance Indicators for Speed Post Performance Management: Fortnightly Review through VCs

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System based Performance Report: Sample web page


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Date: 01 to 15 September 2010

Target Actual

% achieve

ment Target Actual

% achieve

ment Target Actual

% achieve

ment

short term

Target Actual

% achieve

ment

short term

Target Actual

% achieve

ment

short term

Target Actual

% achieve

ment Target Actual

% achievem

ent Target Actual

% achievem

ent

LimitTarget =

100%

Bangalore 1.61 2.48 37% 1.05 2.03 -3% 0.00% 0.15% 85% 5.00% 25.03% -34% 5.00% 24.37% -29% 25.00% 53.26% 62% 50% 27.47% 10% 50% 0.00% -100% 1% 1

Chennai 1.19 2.56 24% 1.05 1.76 25% 0.00% 0.09% 91% 5.00% 22.75% -18% 5.00% 37.02% -113% 25.00% 68.61% 42% 50% 0.01% -100% 50% 0.00% -100% -14% 3

Hyderabad 1.45 2.30 45% 1.05 2.42 -44% 0.00% 0.11% 89% 5.00% 15.99% 27% 5.00% 18.48% 10% 25.00% 65.21% 46% 50% 0.00% -100% 50% 0.00% -100% -9% 2

Kolkata 1.60 3.13 -9% 1.05 2.83 -87% 0.00% 0.15% 85% 5.00% 14.78% 35% 5.00% 92.73% -485% 25.00% 31.67% 91% 50% 0.04% -100% 50% 0.00% -100% -80% 7

Mumbai 1.34 3.25 -15% 1.05 2.88 -93% 0.00% 0.32% 68% 5.00% 28.66% -58% 5.00% 10.94% 60% 25.00% 82.94% 23% 50% 7.01% -72% 50% 0.19% -99% -39% 5

New Delhi 1.51 3.65 -44% 1.05 2.03 -3% 0.00% 0.22% 78% 5.00% 33.19% -88% 5.00% 29.56% -64% 25.00% 79.32% 28% 50% 11.39% -54% 50% 0.59% -98% -37% 4

Noida 1.51 2.79 14% 1.05 4.86 -301% 0.00% 0.12% 88% 5.00% 26.39% -43% 5.00% 66.68% -311% 25.00% 85.59% 19% 50% 0.24% -99% 50% 0.00% -100% -122% 8

Gurgaon 1.51 2.67 22% 1.05 2.79 -83% 0.00% 0.20% 80% 5.00% 39.12% -127% 5.00% 38.16% -121% 25.00% 45.90% 72% 50% 0.15% -99% 50% 0.00% -100% -52% 6

Weightage used

25% 25% 5% 10% 10% 5% 10% 10% 100%

Circle Score Card

Overall score

2.00 = 0% achievement 100 % = 0% achievement

Metro

D+X (TD)D+X (NTD)Share of articles with 'missing'

pin codesShare of 'mis-sorted'

articles (TD)Share of bags without

'correct' bag labelsShare of 'mis-sorted'

articles (NTD)

20 % = 0% achievement1.00 % = 0% achievement

20 % = 0% achievement3.00 = 0% achievement

Overall Ranking

25%= 0% achievement 25%= 0% achievement

Full Scan Compliance (NTD)Full Scan Compliance (TD)

Sample Circle Score Card


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2.56

AugustJuly

2.60

June

2.69

May

2.86

December

3.57

-1.01 days

2010

Impact in terms of improved transit and delivery performance

NTD D+x of 6 metrosAverage of full month, in days

2009

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To ensure sustainability, a Speed Post manual has been developed


Speed Post Manual

How many processing SPCs should exist in a

city?

How to use the to ensure constant

performance monitoring and improvement?

How to ensure standardisation and maximise

throughput and quality?

Which are the right cutoff-times

and processing windows to allow

for maximum next day delivery?

Network topology

Processes within facilities

Network schedule

Performance management

Objectives▪ A relevant document for Speed Post operations across the country▪ To help achive reliable, fast, and standardised Speed Post operations▪ Modular approach allows for flexible updates to keep the Manual up to date

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Incentives for good performers being planned through training


Focus

Recognition of good performers

Training at Bangkok for SPC Managers, ASPs

Find out need for training

Train people to help them to also become star performers

and training

Recognition

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The "look and feel"


Ensure uniform brand/appearance across locations

Develop standardised and consistent, interior and exterior of the building and supporting infrastructure to the line team

Decide on the new tools and technologies to be used and also on how do we upgrade the exiting ones to ensure faster, better services

Develop scheme for recognising star circles/ performersEnsure 100% trained staff on field

Look and feel

Branding Infrastructure Technology Recognition and training

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Speed Post update11

Approach for First Class22

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First Class Mail Network need a revamp as well


Volumes and revenues in First Class Mail are on a declining trend

(- 20 to - 25% over the past 5 years)

Current performance does not match customer expectations, they expect a

substantial improvement in D+x

First Class Mail offers untapped potential that India Post could capture

with high-quality network

The context for change

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Share of traffic and revenue

First class accounts for ~63% of mail volumes and ~34% of revenues, but is on declining volume and revenue trends

498

17

481

2004-05

579

561

18

-5% p.a.

2008-09

465

16449

2007-08

460

17443

2006-07

496

18

478

2005-06

INR crore (%), 2009-10 (Projected)

RegisteredUnregisteredCrore items (%), 2008-09

1,2871,3231,3391,4731,530

-4% p.a.

2008-092007-082006-072005-062004-05

SOURCE: Mail Network Optimization Project, Book of Information 2008-2009, MIS reports, Costing department

1 Revenue figures are for First Class and Second Class Mail as they are not separately tracked

Development of First Class over time

Speed Post 74 (11)

International 17 (3)

Second classmail 150 (23)

First class mail 413 (63)

Postal 654 (100)

Volume (crore)

Speed Post 736 (21)

International 307 (9)

Second classmail 1,215 (36)

First class mail 1,178 (34)

Postal 3,436 (100)

Revenue (INR crore) 1

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4.8

2.8

NTD delivery metro to

non-metro

TD delivery

1.5

2.5

3.5

NTD delivery metro

to metro 2.0

2.5

3.2

6.5

2.0

2.8

4.0

SOURCE: Survey of 120 retail customers and 38 corporate customers (30/08/2010 to 08/09/2010), Project team test letter program

2.8

3.5

1.6

2.5

3.4

2.5

1.9

4.2

3.3

1.7

1.8

1.6

Customers are aware of India Post’s insufficient performance and expect improvements in the range of 2 to 4 days for delivery

Unregistered mailN = 51 (non-bulk)

Registered mailN = 69 (non-

bulk) Expected performance

Perceived performance

Actual performance1

1 Performance based on test-letter program conducted by Project Team from 31/08/10 to 06/09/10 (total sample size: 438, of which 238 unregistered letters and 200 registered letters)

2.9

N/A

2.2

1.7

2.9

N/A

2.9

3.5

N/A

0.6

0.7

0.8

Bulk mailN = 38 (bulk)

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India Post is in a good position to capture future growth opportunities in case it can turnaround its First Class mail business


▪ Indian mail market is underpenetrated with Indians receiving less than 10 mail articles/person vs. 200 articles/person in Germany and 600 articles/person in US

Untapped growth

potential can be captured …

…by leveraging India Post’s unique and

large network

▪ India Post has a strong network with ~155,000 post offices, which means that with a ratio of one office for ~7,000 Indian citizens it provides a very dense service infrastructure

▪ Majority of ordinary non-bulk mail is posted through letter boxes. With ~685,000 letter boxes across the country, India Post provides a wide network

Capturing the growth opportunity in the future will only happen if quality is improved, which will require an

operational transformation of the First Class product segment

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For First Class, we will focus on the same elements as for SpeedPost, while recognizing differences


What is the right network topology?

▪ Higher fragmentation of network (more facilities, less concentrated volumes)

▪ Higher intra-city complexity (more facilities, less standardized flow)

How to measure India Post's

performance?

▪ Lack of objective data hinders performance measurement▪ Low performance management orientation and lack of

consistency of existing reports for unregistered mail

▪ Higher planning complexity (multiple transport modes involved)

▪ Lower planning capacityWhat is the right

network schedule?

▪ Relative importance of processes within sorting facilities lower in First Class

▪ Relevance of sorting automation and of improvements to delivery preparation higher in First Class (higher volumes)

What are the right processes?

Main differences between First Class and Speed Post

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Proposed approach for First Class wave – Initial efforts will focus on topology (country-wide and intra-city) and network scheduling

29 062215080125181104272013

Dec-10Nov-10Oct-10Sep-10

Develop strategy for sorting machines

Codify best practices

Processes (sorting) – Implement First Class manual

and develop additional improvements in

consolidated facility

Build comprehensive topology model

Build KPI architecture based on SpeedPost and redesign test-letter program

Build preliminary topology model

Define optimal Network Schedule

(between 6 metros)

Processes – Build First Class manual

based on SpeedPost

Manual

Processes (delivery) – Identify improvements in delivery preparation

Define facility for consolidation1 in the

6 metros

SOURCE: Mail network optimisation project

▪ Continued support on Speed Post

“Getting the core right” in country-wide

and intra-city topology is a

prerequisite to achieve long-term

impact as it will create the basis on which

scheduling and process improvements

can be built on and sustained

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First Class Mail Network Optimization: Study in Progress


▪ Study of mail profile in 6 cities currently undergoing

▪ Mapping of P.O.s to mail offices undertaken

▪ Level I and II sorting offices being planned

▪ Delivery Office process optimization pilot being undertaken in metro cities

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Any questions or comments?

Documents

Mail Network Optimization Project